The overall goal of this Program Project is to enable prediction of the molecular functions, e.g., substrate specificity and/or specific chemical reaction, of enzymes in the enolase and AH superfamilies. The role of the computational project is to integrate and apply bioinformatic characterization of sequences, structures, and functions, comparative modeling of protein structures, and ligand docking to help achieve this goal. In close collaboration with the experimental investigators, we envision an iterative cycle providing multiple parallel and serial paths to obtaining high quality information useful for functional prediction. Applying our approaches to enzymes previously characterized structurally and mechanistically will serve as controls for evaluating computational results. Modeling sequences of unknown function will aid in the selection of targets for experimental structural characterization and biochemical testing; conversely, results from experimental activity screening with libraries of substrates will be used to refine clustering of superfamily sequences and structures, and to provide additional restraints for modeling and docking exercises. Experimental solution of liganded structures targeted by the most promising of our predictions will be invaluable for the evaluation of docking results and methodologies. Conversely, loop modeling exercises may aid in interpreting regions of structures that cannot be resolved by x-ray crystallography. We expect that this collaboration between the experimental and computational groups will also result in improved tools and methodologies for semi-automated prediction of molecular function, specifically for the enolase and AH superfamilies, and generally for the wider set of unknown or under-characterized open reading frames (ORFs) coming out of the genome projects.